Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Asymptotic solutions of the planar squeeze flow of a casson fluid(American Institute of Physics Inc. subs@aip.org, 2018) Singeetham, P.K.; Vishwanath, V.K.In this study, we present the squeeze flow of viscoplastic fluid using Casson model between parallel plates that are approaching each other with constant squeeze motion. Based on the technique of matched asymptotic expansions, we develop the complete asymptotic solutions for the squeeze flow of viscoplastic Casson fluid model. We derive the expressions for velocity, stress and squeeze force. The effects of the yield threshold on the pseudo-yield surface that separates the sheared and plastic zones and squeeze force for different values of non-dimensional yield stress have been investigated. © 2018 Author(s).Item Asymptotic Solutions of the Planar Squeeze Flow of a Herschel-Bulkley Fluid(Institute of Physics Publishing helen.craven@iop.org, 2018) Singeetham, P.K.; Vishwanath, V.K.In this study, we present the analysis of the squeeze flow of a Herschel-Bulkley fluid between parallel plates that are approaching each other with a constant squeeze motion. The classical lubrication analysis predicts the existence of a central unyielded zone bracketed between near-wall regions. This leads to the well-known squeeze flow paradox for viscoplastic fluids. Since the kinematic arguments show that there must be a finite velocity gradient even in the unyielded zone, thereby precluding the existence of such regions. This paradox may, however, be resolved within the framework of a matched asymptotic expansions approach where one postulates separate expansions within the yielded and apparently unyielded (plastic) zones. Based on the above technique, we circumvent the paradox, and develop complete asymptotic solutions for the squeeze flow of a Herschel-Bulkley fluid. We derive expressions for the velocity, pressure and squeeze force. The effects of the yield threshold on the pseudo-yield surface that separates the sheared and plastic zones, and squeeze force for different values of non-dimensional yield stress have been investigated. © Published under licence by IOP Publishing Ltd.Item Inertia Effects in the Planar Squeeze Flow of a Bingham Fluid: A Matched Asymptotics Analysis(Springer, 2021) Singeetham, P.K.; Vishwanath, V.K.The effects of inertia on the squeeze flow of a Bingham fluid between two approaching parallel plates with a constant squeeze velocity is investigated using matched asymptotic expansions. This analysis is an extension to the prior study of Muravleva (2015), who has investigated the planar squeeze flow of a Bingham fluid in the absence of inertia. In the present study, the expressions for the shear stress field, velocity, pressure field and squeeze force are derived. The combined effects of the fluid inertia and yield stress on the pressure field and squeeze force are investigated. We found that the pressure and eventually squeeze force increases with increase in Reynolds number. The squeeze force decreases with an increase in the value of the gap aspect ratio. © 2021, Springer Nature Singapore Pte Ltd.Item From Pixels to Prognosis: Exploring from UNet to Segment Anything in Mammogram Image Processing for Tumor Segmentation(Institute of Electrical and Electronics Engineers Inc., 2024) Hithesh, M.R.; Vishwanath, V.K.Breast cancer, is the most prevalent form of cancer among women globally accounting for nearly one in four of all new cancer cases. This high prevalence makes breast cancer the second leading cause of death among women making early detection of breast cancer crucial for reducing mortality rates. Mammography, a widely employed medical imaging technique, emerges as a front-line defense against breast cancer. The research aims to achieve pivotal objectives: Firstly, to examine the Segment Anything Model (SAM), created by MetaAI in 2023, and also discuss the model's use in medical image segmentation. Secondly, the study aims to conduct a comprehensive comparative analysis of SAM's segmentation capabilities with other existing segmentation models for medical images. The unique strength of the research lies in incorporating both mass and calcification mammograms within the diverse Curated Breast Imaging Subset of DDSM (CBIS-DDSM) dataset this acknowledges the varied nature of breast cancer, exposing the segmentation models to a wide range of scenarios. Through augmenting the dataset with vertical, horizontal, and rotational transformations, this enables accurate identification and isolation of Region of Interests (RoIs) in mammograms, for robust model training for real-world breast cancer diagnosis. The study investigates different segmentation models for medical image segmentation, with an emphasis on prompt-based (SAM), Encoder-Decoder (UNet, UNet++, Attention-UNet, SegNet) models. The study extends to evaluating these models based on Key Performance Indicators (KPIs) such as Dice score, Intersection over Union (IoU) and Accuracy. The insights gained from this research have broader implications for the application of more accurate segmentation in medical image analysis, and making a significant contribution to the continuous efforts to improve breast cancer diagnostic methodologies. © 2024 IEEE.